Connor Mccormick is a founder and AI strategist who builds production-grade, enterprise-scale ML systems with a focus on generative AI and LLM-powered workflows. With four years of hands-on experience across startups and Fortune 500s, he has led product and go-to-market engineering for LLM fine-tuning and deployment platforms and now runs his own consultancy and legal-tech startup. His background spans full-stack engineering, ML systems, and cloud infrastructure, enabling end-to-end delivery from problem framing to production. Notably, he architected explainability frameworks and SDKs that helped bring enterprise GPU-accelerated LLMs to market and contributed to award-winning automated support systems at Cisco. Based in the San Diego area and educated at UC Berkeley, he combines technical depth with practical product instincts to help organizations adopt LLMs that drive measurable business outcomes.
4 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Cognitive Science, Bachelor of Arts - BA, Cognitive Science at University of California, Berkeley
Master of Applied Machine Learning, Master of Applied Machine Learning at UC Berkeley School of Information
Chinese Language and Literature, Chinese Language and Literature at Fudan University
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